Stability Analysis of Biological Network Topologies during Stochastic Simulation

Davide Prandi; Tommaso Mazza

4th International ICST Conference on Simulation Tools and Techniques

Research Article

Stability Analysis of Biological Network Topologies during Stochastic Simulation

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@INPROCEEDINGS{10.4108/icst.simutools.2011.245590,
    author={Davide Prandi and Tommaso Mazza},
    title={Stability Analysis of Biological Network Topologies during Stochastic Simulation},
    proceedings={4th International ICST Conference on Simulation Tools and Techniques},
    publisher={ICST},
    proceedings_a={SIMUTOOLS},
    year={2012},
    month={4},
    keywords={Graph algorithms Monte Carlo Biology and genetics},
    doi={10.4108/icst.simutools.2011.245590}
}

Davide Prandi
Tommaso Mazza
Year: 2012
Stability Analysis of Biological Network Topologies during Stochastic Simulation
SIMUTOOLS
ICST
DOI: 10.4108/icst.simutools.2011.245590

Davide Prandi¹^,*, Tommaso Mazza²

1: CoSBi
2: Centre for Integrative Biology (CIBIO) University of Trento

*Contact email: prandi@cosbi.eu

Abstract

Recent advances in the stochastic simulation of biological systems have exploited the weighted dependency di-graph as a compact representation of the computational workload. It was largely used to represent the causal relationships among reactions and then to determine their cause-eect implica- tions. Although critical for several applications, the topol- ogy of the dependency graph has been little studied so far. Here, we make use of some network topology indices to de- tect and characterize the important reactions of two real case studies. We measure the stability of such indices over time and make a case for considering them in parallel stochastic simulation.

Keywords: Graph algorithms Monte Carlo Biology and genetics

Published: 2012-04-13
Publisher: ICST

: http://dx.doi.org/10.4108/icst.simutools.2011.245590